III.3 Related work 141 ε Probability ratio 0 Temporal di!erence error , Clipping parameter 1 Bias-variance balance parameter Sewer mains maintenance optimisation: h Health vector L Sewer main length ∆L Sewer main segment length ω Number of segments in a sewer main d¯ Vector of severity level per segment in a sewer main 1k Total number of pipe segments at each severity level k ↓S III.3 Related work Over the past two decades, the need for integral sewer asset management has become evident (Abraham, Wirahadikusumah, Short, et al., 1998), highlighting the necessity of understanding deterioration mechanisms and developing predictive models for proactive and strategic sewer maintenance (R. Fenner, 2000). Sewer asset management encompasses maintenance, rehabilitation, and inspection, and has been investigated through various methodologies, encompassing risk-based strategies, multi-objective optimisation, MDPs, analysis of network structure, Machine Learning applications, decision-support frameworks, and Reinforcement Learning. An overview of each approach is provided below. Risk-based Arisk-based approach evaluates the potential for loss or negative outcomes due to uncertainty. Arthur and Crow, 2007 focus on serviceability, suggesting proactive maintenance of assets to prevent sewer overflow, flooding, and tra"c disruptions. Fuchs-Hanusch, Günther, Möderl, et al., 2015 concentrate on cause-e!ect relationships to aid inspection planning, employing logistic regression to estimate the probability of sewer failure and its negative e!ects on the system’s hydraulic performance. Baah, Dubey, Harvey, et al., 2015 utilises a risk matrix and a weighted-sum multi-criteria decision matrix for the assessment of consequences and risks associated with sewer main failure. Fontecha, Akhavan-Tabatabaei, Duque, et al., 2016 addresses sediment-related blockages, deriving maintenance costs per time unit through a convex non-linear function and a homogeneous Poisson process. Lee, Park, Baek, et al., 2021 focus on sewer inspection, employing a risk matrix-based method to assess economic, social, and environmental impacts.
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